As the core vehicle for preserving and transmitting traditional Chinese medicine（TCM） academic thought and clinical experience， the establishment of a robust quality evaluation system for TCM clinical case reports is a crucial component in the current standardization and modernization of TCM. Based on the practical experience of constructing the China Clinical Cases Library of Traditional Chinese Medicine by the China Association of Chinese Medicine， this study conducted a comprehensive analysis of critical challenges， including insufficient authenticity and unfocused evaluation criteria. It proposed a three-dimensional evaluation framework grounded in the structure-process-outcome logic， encompassing three dimensions of authenticity and standardization， characteristics and advantages， application and translational impact. This framework integrated 12 key evaluation indicators in a systematic manner. The model preserved the academic characteristics of TCM syndrome differentiation and treatment， while aligning with modern scientific research standards， achieving a balance between individualized TCM experience and standardized evaluation. Concurrently， this study provided theoretical foundations and methodological guidance for evaluating the quality of TCM clinical cases， contributing significantly to the inheritance of TCM knowledge， evidence-based practice， and the reform of talent evaluation mechanisms.

Objective Objective To analyze the potential spatial factors affecting the genetic differentiation of Oncomelania hupensis robertsoni in Yunnan Province. Methods A total of 13 administrative villages were selected from schistosomiasis-endemic areas of Yunnan Province as O. hupensis snail sampling sites. At least 200 snails were collected in each site, and the spatial variable data of each site were recorded, including longitude, latitude and altitude. Thirty active and Schistosoma japonicum uninfected O. hupensis snails were selected from each sampling site by means of the crawling method and the cercarial shedding method. Genomic DNA was extracted from O. hupensis snails. Following PCR amplification, purification of PCR amplification products and sequencing, the gene sequences of O. hupensis snail samples were spliced and edited using the DNAstar software and the NCBI database to yield the complete mitochondrial sequences of O. hupensis snails at each sampling site, and the mitochondrial genetic distance matrix of O. hupensis robertsoni was calculated at each sampling site. The geographical coordinates of each sampling site were marked using the software ArcGIS 10.2, and the straight-line geographical distance between each sampling site was calculated. The altitude difference, longitude difference and latitude difference between each sampling site were calculated using the Excel software, and the correlation between the mitochondrial genetic distance matrix of O. hupensis robertsoni and each spatial variable matrix was examined by using the Mantel test at 13 sampling sites in Yunnan Province. Results Among the 13 O. hupensis snail sampling sites in Yunnan Province, the largest mitochondrial genetic distance of O. hupensis robertsoni snail populations was seen between Anding Village, Nanjian Yi Autonomous County and Caizhuang Village, Midu County (26.244 2), and the largest geographical distance was seen between Dongyuan Village, Gucheng District and Cangling Village, Chuxiong County (272.64 km). The highest altitude difference was seen between Anding Village, Nanjian Yi Autonomous County and Dongyuan Village, Gucheng District (1 086.10 m), and the largest longitude difference was found between Qiandian Village, Eryuan County and Cangling Village, Chuxiong County (1.86°), while the largest latitude difference was measured between Leqiu Village, Nanjian Yi Autonomous County and Dongyuan Village, Gucheng District (1.81°). In addition, the mitochondrial genetic distance of O. hupensis robertsoni snail populations was positively correlated with altitude at 13 snail sampling sites in Yunnan Province (r = 0.542 8, P < 0.001), and showed no significant correlations with geographical distance (r = 0.093 4, P > 0.05), longitude (r = −0.199 5, P > 0.05) or latitude (r = 0.205 7, P > 0.05). Conclusion Altitude may be a potential spatial factor affecting the genetic differentiation of O. hupensis robertsoni in Yunnan Province.

Objective:To construct a prediction model for the risk of sarcopenia in middle-aged and elderly patients with knee osteoarthritis (KOA) based on machine learning, and to provide a basis for carrying out the prevention of sarcopenia in patients with KOA.Methods:Clinical data of KOA patients from three tertiary hospitals in Guangdong Province were collected between December 2023 and September 2024 using a convenience sampling method. The data were randomly split into training and test sets at an 8:2 ratio, with the occurrence of sarcopenia as the outcome variable. Risk prediction models for sarcopenia were constructed using eight machine learning algorithms: logistic regression, K-nearest neighbors, support vector machine, decision tree, neural network, random forest, gradient boosting machine (GBM), and eXtreme gradient boosting. Model performance was evaluated based on metrics including the area under the receiver operating characteristic curve (AUC), accuracy, precision, sensitivity, specificity, and F1 score. The optimal model was selected, and feature importance was visualized using the Shapley Additive exPlanations (SHAP) method.Results:Data from 640 KOA patients were analyzed, 143 males and 497 females, (67.51± 7.72) years, with 136 cases (21.25%) developing sarcopenia. All eight prediction models showed high AUC values, with the GBM model demonstrating the best performance. Its metrics included an AUC of 0.926 (95% CI 0.874 - 0.965), accuracy of 0.852, precision of 0.611, sensitivity of 0.815, specificity of 0.861, and F1 score of 0.698. SHAP analysis identified body mass index, calf circumference, body fat percentage, WOMAC score, and age as the most important predictive features. Conclusions:The GBM-based risk prediction model for sarcopenia in middle- aged and elderly KOA patients demonstrated optimal performance, enabling healthcare professionals to accurately and promptly identify high-risk groups among these patients and to develop effective, evidence-based intervention strategies.

Objective To investigate the effect and mechanism of solute carrier family 39 member 14(SLC39A14)on iron overload-induced insulin resistance in HepG2 cells.Methods HepG2 cells were cultured in vitro,and different concentrations of ferric ammonium citrate(FAC)were added to detect cell viability by CCK-8,calcein-AM was used to detect unstable iron pools(LIP),mi-tochondria were observed by transmission electron microscopy,and insulin resistance was detected by cellular glucose consumption,as well as the expression of SLC39A14 protein and mRNA.Subsequently,Ferrostatin-1(Fer-1)was added to detect reactive oxygen spe-cies(ROS),malondialdehyde(MDA)and glutathione(GSH).Finally,small interfering RNA(siRNA)technology was used to knock down the expression of SLC39A14 to observe whether oxidative stress and insulin resistance indices changed.Results After FAC inter-vention,cell viability decreased,the LIP level increased,and glucose consumption reduced.Additionally,the protein and mRNA expres-sion of SLC39A14 was upregulated.Compared with the FAC group,the co-treatment of FAC and Ferrostatin-1 ameliorated the intracel-lular oxidative stress by decreasing the levels of ROS and MDA and increasing the levels of GSH,down-regulating the protein and mRNA expression of SLC39A14,and increasing the glucose consumption,thereby alleviating the onset of insulin resistance.After knockdown of SLC39A14,the levels of oxidative stress and insulin resistance in HepG2 cells in the FAC+SLC39A14 knockdown group were further im-proved compared with those in the FAC group.Conclusion FAC intervention caused the development of insulin resistance in HepG2 cells by a mechanism that may be related to activation of SLC39A14.

Objective To investigate the feasibility and accuracy of an ultrasound-based transfer learning artificial intelligence model in predicting the malignancy probability of partially cystic thyroid nodules(PCTN).Methods A retrospective analysis was conducted on 246 patients with PCTN who had definitive pathological results and were admitted to Weihai Municipal Hospital,Cheeloo College of Medicine,Shandong University from January 2021 to December 2023.Patients were randomly divided into training and test cohorts at a ratio of 7:3.Ultrasonic image features of PCTN were evaluated,and independent risk factors were identified using multivariate logistic regression analysis,with the area under the curve(AUC)subsequently calculated.Additionally,five different pre-trained models-Inception_v3,EfficientNet,VGG19,ResNet50,and DenseNet121-were selected for transfer learning after data preprocessing using the PyTorch framework in Python.The AUC values of these models were calculated and compared.Results Solid portion greater than 50%,eccentric acute angle,ill-defined margin,spiculated or microlobulated margin,rim calcification,and microcalcification exhibited statistically significant differences(P<0.05)in distinguishing between benign and malignant PCTN.The AUC value derived from these independent risk factors was 0.843.Furthermore,among the five transfer learning models evaluated,the ResNet50 model demonstrated the highest diagnostic efficiency,achieving an AUC value of 0.903 2.Conclusion The ultrasound-based transfer learning artificial intelligence model demonstrated superior performance compared to traditional ultrasound image evaluation methods,enabling accurate prediction of the nature of PCTN and thereby reducing unnecessary ultrasound-guided fine needle biopsies.

Objective:To analyze the differences in endoscopic and pathological features in autoimmune gastritis (AIG) patients with and without Helicobacter pylori ( HP) infection, and to explore the effects of HP on the clinical manifestations and disease development in AIG patients. Methods:From January 2022 to April 2024, 174 AIG patients who visited Beijing Hospital and met the 2022 AIG diagnostic criteria established by Japanese Gastroenterological Endoscopy Society were enrolled and divided into the HP-infected group (including current and previous infection, 77 cases) and the HP-unifected group (97 cases). The general clinical data, laboratory examinations endoscopic findings, and pathological characteristics of the two groups were analyzed. Independent sample t-test and chi-square test were used for statistical analyses. Results:The vitamin B 12 level of HP-infected group was higher than that of HP-unifected group ((573.81±460.77) ng/L vs. (411.86±335.00) ng/L), and the difference was statistically significant ( t=-2.57, P=0.011). The average red blood cell volume of HP-infected group was lower than that of HP-unifected group ((87.30±8.86) fL vs. (98.50±49.82) fL), and the difference was statistically significant ( t=2.16, P=0.033). The proportion of intestinal metaplasia in gastric fundus in HP-infected group was lower than that in HP-unifected group (50.6% (39/77) vs. 73.2% (71/97)), and the difference was statistically significant ( χ2=9.38, P=0.002). Conclusion:HP infection in AIG patients may delay the malabsorption of vitamin B 12 and the occurrence of intestinal metaplasia in gastric fundus.

Objective To investigate the feasibility and accuracy of an ultrasound-based transfer learning artificial intelligence model in predicting the malignancy probability of partially cystic thyroid nodules(PCTN).Methods A retrospective analysis was conducted on 246 patients with PCTN who had definitive pathological results and were admitted to Weihai Municipal Hospital,Cheeloo College of Medicine,Shandong University from January 2021 to December 2023.Patients were randomly divided into training and test cohorts at a ratio of 7:3.Ultrasonic image features of PCTN were evaluated,and independent risk factors were identified using multivariate logistic regression analysis,with the area under the curve(AUC)subsequently calculated.Additionally,five different pre-trained models-Inception_v3,EfficientNet,VGG19,ResNet50,and DenseNet121-were selected for transfer learning after data preprocessing using the PyTorch framework in Python.The AUC values of these models were calculated and compared.Results Solid portion greater than 50%,eccentric acute angle,ill-defined margin,spiculated or microlobulated margin,rim calcification,and microcalcification exhibited statistically significant differences(P<0.05)in distinguishing between benign and malignant PCTN.The AUC value derived from these independent risk factors was 0.843.Furthermore,among the five transfer learning models evaluated,the ResNet50 model demonstrated the highest diagnostic efficiency,achieving an AUC value of 0.903 2.Conclusion The ultrasound-based transfer learning artificial intelligence model demonstrated superior performance compared to traditional ultrasound image evaluation methods,enabling accurate prediction of the nature of PCTN and thereby reducing unnecessary ultrasound-guided fine needle biopsies.

Objective To investigate the effect and mechanism of solute carrier family 39 member 14(SLC39A14)on iron overload-induced insulin resistance in HepG2 cells.Methods HepG2 cells were cultured in vitro,and different concentrations of ferric ammonium citrate(FAC)were added to detect cell viability by CCK-8,calcein-AM was used to detect unstable iron pools(LIP),mi-tochondria were observed by transmission electron microscopy,and insulin resistance was detected by cellular glucose consumption,as well as the expression of SLC39A14 protein and mRNA.Subsequently,Ferrostatin-1(Fer-1)was added to detect reactive oxygen spe-cies(ROS),malondialdehyde(MDA)and glutathione(GSH).Finally,small interfering RNA(siRNA)technology was used to knock down the expression of SLC39A14 to observe whether oxidative stress and insulin resistance indices changed.Results After FAC inter-vention,cell viability decreased,the LIP level increased,and glucose consumption reduced.Additionally,the protein and mRNA expres-sion of SLC39A14 was upregulated.Compared with the FAC group,the co-treatment of FAC and Ferrostatin-1 ameliorated the intracel-lular oxidative stress by decreasing the levels of ROS and MDA and increasing the levels of GSH,down-regulating the protein and mRNA expression of SLC39A14,and increasing the glucose consumption,thereby alleviating the onset of insulin resistance.After knockdown of SLC39A14,the levels of oxidative stress and insulin resistance in HepG2 cells in the FAC+SLC39A14 knockdown group were further im-proved compared with those in the FAC group.Conclusion FAC intervention caused the development of insulin resistance in HepG2 cells by a mechanism that may be related to activation of SLC39A14.

Idiopathic gingival fibromatosis is a rare, benign condition of unknown etiology characterized by extensive gingival overgrowth. This case reports a severe skeletal Class Ⅱ adult female patient with idiopathic gingival fibromatosis. The patient underwent multidisciplinary treatment involving periodontics, orthodontics, and orthognathic surgery, resulting in remarkable crown height elongation, substantial improvements in occlusal function and aesthetics, and stable long-term follow-up outcomes. This case provides a reference for future clinical practice.
Humans ; Female ; Malocclusion, Angle Class II/complications* ; Fibromatosis, Gingival/complications* ; Adult ; Orthodontics, Corrective ; Orthognathic Surgical Procedures

Objective:To investigate the role of heat shock transcription factor 1(HSF1)in hepatitis B virus X protein(HBx)-driven migration and invasion of hepatocellular carcinoma(HCC)cells,and to preliminarily explore the mechanism of HSF1 mediating HBx-driven HCC progression.Methods:4D label-free quantitative proteomics and Western blot were used to analyze the effect of HBx on HSF1 expression.HBx was overexpressed in the HCC cell lines Huh7 and MHCC97H,and its impact on the mRNA and protein levels and stability of HSF1 was assessed by RT-PCR and Western blot.The Cancer Genome Atlas database was used to analyze the expres-sion of HSF1 in hepatitis B virus(HBV)-associated HCC tissues and its relationship with tumor stage/grade and patient prognosis,and Western blot was used to measure the expression of HSF1 in HBV-associated HCC tissues.HBx was overexpressed in HCC cells,fol-lowed by HSF1 knockdown or cell treatment with the HSF1 inhibitor KRIBB11,and Transwell migration and invasion assay,scratch as-say,and F-actin staining experiment were performed to analyze the role of HSF1 in HBx-driven HCC cell migration and invasion.GEO and HCMDB datasets were used to identify the downstream target of HSF1,and the role of downstream target c-Myb in HSF1-me-diated HBx-driven HCC progression.Results:HBx upregulated HSF1 protein levels without significantly affecting its mRNA expres-sion,through enhancing HSF1 protein stability.HSF1 was highly ex-pressed in HBV-associated HCC tissues,and its elevated expres-sion correlated with tumor stage/grade and poor prognosis.HBx overexpression significantly promoted the migration,invasion,wound-healing capacity,and pseudopodia formation capacity of Huh7 and MHCC97H cells,while HSF1 knockdown or KRIBB11 treatment significantly attenuated the HBx-driven migration and in-vasion of HCC.HSF1 promoted the expression of the metastasis-associated protein c-Myb,and c-Myb overexpression in HSF1-knock-down HCC cells restored the promotive effect of HBx on HCC cell migration and invasion.Conclusion:HBx enhances HSF1 protein stability to promote its expression.Upregulation of c-Myb by HSF1 plays a pivotal role in HBx-driven HCC cell migration and inva-sion.Targeting HSF1 may help to delay the progression of HBV-associated HCC.